The present invention relates to a method and device for estimating the likelihood that an image of a body or body part obtained through Diffusion Tensor Imaging (DTI) or Diffusion Weighted Imaging (DWI) contains a lesion and further estimating the likelihood that the lesion is cancer.
The known technique of diffusion imaging is disclosed in U.S. Patent Application Publication No. 20100298692A1, the disclosure of which is incorporated herein by reference.
Background in breast MRI methods and terminology: The invention is applicable to a plurality of parts of the body. For the sake of clarity, the background and description will be described in terms of detection and diagnosis of breast cancer. It is to be understood that this description is for illustrative purposes and does not restrict the field of application to any specific form of cancer or any specific part of the body.
Diffusion Tensor Imaging (DTI) measures the magnitude and direction of random motion of water molecules and requires the acquisition of signals in at least 6 directions. If the random motion is assumed to be isotropic, then a simplified form of DTI, called Diffusion Weighted Imaging (DWI) can be used, which only requires acquisition of signal in 3 directions. A qualitative representation of a diffusion image can be obtained using a single direction.
The physiological basis of using DWI/DTI for cancer diagnosis is that the densely packed cells within a cancer restrict the normal random motion (Brownian motion) that occurs within all cells. A low level of random motion within the cells is an indicator of cancer which is different from the vascularization characterized by dynamic contrast imaging (DCE), the current standard for breast MR detection and diagnosis. The most common diagnostic values obtained from diffusion analysis are:                1. The apparent diffusion coefficient (ADC): an aggregate measure of the degree of diffusion that can be derived from the three directions used for DWI. ADC maps can be used by radiologists to distinguish areas with low Brownian motion that are suspicious for cancer. Areas of low ADC values are suspicious for breast cancer because the may indicate high cellular, low diffusion region within a malignant lesions. [Eyal E., Shapiro-Feinberg M., Furman-Haran E., Grobgeld D., Golan T., Itzchak Y, Catane R, Papa M., Degani H. “A Novel MRI method for Breast Cancer Detection Based on Diffusion Tensor Tracking of the Ductal Tree.” Paper C-0329. Proc ISMRM 19, May 2010]        2. Fractional anisotropy (FA): an aggregate measure of anisotropy that requires the six or more directions used for DTI. FA maps can be used by radiologists to distinguish areas of strong and weak anisotropy.                    The following gives a summary of the use of tensor eigenvalues as applied to diffusion MR imaging:                            Apparent diffusion coefficient (also known as the mean diffusivity, Dav) describes the degree of mobility or restriction of water molecules, and is given byADC=(λ1+λ2+λ3)/3 mm2/second,                where λ1, λ2, λ3 are the maximum, intermediate, and minimum diffusion tensor eigenvalues, respectively. The eigenvalues describe the magnitude or rate of diffusion along each of the three principal axes of the diffusion tensor ellipsoid (in mm2/second).                Fractional anisotropy is a unitless measure of the degree of directionality of intravoxel diffusivity, calculated by                                                
  FA  =            √              [                                            (                                                λ                  1                                -                                  λ                  2                                            )                        2                    +                      (                                                            (                                                            λ                      2                                        -                                          λ                      3                                                        )                                2                            +                              (                                                      (                                                                  λ                        1                                            -                                              λ                        3                                                              )                                    2                                ]                                                                        √        2            ⁢              √                  [                                    λ              1              2                        +                          λ              2              2                        +                          λ              3              2                                ]                                                                                    “For isotropic diffusion (λ1=λ2=λ3), FA is zero, and in the case of high anisotropy where there is a strongly preferred direction of diffusion λ1>>λ2>λ3”. [Partridge, S C, Ziadloo A, Murthy R, White S W, Peacock S, Eby P R, DeMartini W B, Lehman C D. “Diffusion Tensor MRI: Preliminary Anisotropy Measures and Mapping of Breast Tumors,” Journal of Magnetic Resonance Imaging, February 2010, 31:339-347]                                                
The sensitivity of the DWI sequence to water motion can be varied by changing the gradient amplitude, the duration of the applied gradient, and the time interval between the paired gradients. On clinical MR scanners, the diffusion sensitivity is easily varied by changing the parameter known as the “b” value, which is proportional to these three factors. When the b value is changed, it is usually the gradient amplitude, rather the duration or time intervals between gradients, that is altered. [Koh D-M, Collins DJ. “Diffusion-Weighted MRI in the Body: Applications and Challenges in Oncology.” AJR June 2007; 188:1622-1635]
The ADC map can be computed from the DWI or DTI data using at least two different b values. When the ADC value is computed using two b values, the following equation is used, where SDWI is the combined DWI (geometric average of unidirectional high b diffusion-weighted images), and S0 is the T2-weighted b=0 s/mm2 reference image. [Partridge, S C, DeMartini W B, Kurland B F, Eby P R, White S W, Lehman C D. “Differential Diagnosis of mammographically and Clinically Occult Breast Lesions on Diffusion-Weighted MRI.” Journal of Magnetic Resonance Imaging, Mar 2010, 31:562-570]
  ADC  =            -              1        b              ⁢          ln      ⁡              (                              S            DWI                                S            0                          )            
High b value of 1000 has been used by some researchers [Guo Y, Cai Y-Q, Cai Z-L, Gao Y-G, An N-Y, Ma L, Mahankali S, Gao, J-H. “Differentiation of Clinically Benign and Malignant Breast Lesions using Diffusion-Weighted Imaging,” Journal of Magnetic Resonance Imaging, 2002, 16:172-178 (2002)], [Yili Z, Xiaoyan H, Hongwen D, Yun Z, Xin C, Peng W, Youmin G. “The value of diffusion-weighted imaging in assessing the ACD changes of tissues adjacent to breast carcinoma.” BMC Cancer 2009, 9:18: 1-10. (available at http://www.biomedcentral.com/1471-2407/9/18)], while Partridge, et al have used a high b value of 600, noting that:
“It has been shown that the b-value that provides the highest signal-to-noise ratio for a spin-echo diffusion-weighting sequence is equal to 1.1/ADC [citing [Jones D K, Horsfield M A, Simmon A. “Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging,” Magn Reson Med 1999; 42:515-525.]] For breast imaging, with typical reported ADC values of 1.6-2.0×103 mm2/s for normal tissue, this corresponds to an optimal diffusion weighting of approximately b=600 s/mm2.” Partridge, S C, DeMartini W B, Kurland B F, Eby P R, White S W, Lehman C D. “Quantitative Diffusion-Weighted Imaging as an Adjunct to Conventional Breast MRI for Improved Positive Predictive Value,” AJR December 2009; 193-1716-1722].
Non-zero low values of b, such as b=100, are sometimes used in place of b=0.                The selection of a low b-value larger than zero provides suppression of large vessels which makes lesions more conspicuous. The calculation of the tissue ADC can be more accurate when starting with even higher b-values like 100 or 200 to omit the contribution of flow and microvascular effects.        
[Graessner, “Frequently Asked Questions: Diffusion Weighted Imaging (DWI),” available at: http://www.medical.siemens.com/siemens/it_IT/gg_mr_FBAs/files/MAGNETOM_World/Application_Tips/MAGN ETOM_Flash—46/Frequently_Asked_Questions_Diffusion-Weighted_Imaging.pdf].
Clinical MR systems generate diffusion weighted images in three directions, typically slice, frequency (read) and phase encoded. [Charles-Edwards E and deSousa, N, “Diffusion-weighted magnetic resonance imaging and its application to cancer,” Cancer Imaging (2006),6. 135-143] The minimum number of scans to obtain the ADC from the three orthogonal directions is 4: one scan at b=0 plus three unidirectional scans at high b value taken in the three orthogonal directions. [“D:the Diffusion of Water” (Chapter 7), Wheeler-Kingshott, et al. from: Quantitative MRI of the Brain (P. Tufts ed., 2003, John Wiley & Sons, Ltd. ISBN: 0-470-84721-2]
DCE and DWI/DTI measure different physiological characteristics and can provide complementary information.
Images derived from DCE sequences are used to evaluate the enhancement pattern of a contrast agent (gadolinium) into and out of a lesion. Clinical evaluation is based on both the shape of the enhancement pattern (morphology) and the rate of flow of the contrast agent into and out of the lesion (kinetics). Both morphology and kinetics provide information about the vascularization that feeds the lesion; the physiological rationale for DCE is that cancerous lesions require increased vascularization to feed the growing tumor. Increased vascularization indicated by morphological and kinetic patterns of the contrast agent is regarded as a suspicious marker.
Images derived from DWI/DTI characterize random motion within cells as an indicator of cellular density.
Clinical advantages and problems associated with DWI are summarized as follows:                Dynamic contrast enhanced (DCE) MRI is used for detection and diagnosis of breast cancer only for special cases, presumably because of its relatively high costs, significant false positive rates, discomfort and risk of adverse effects, including nephrogenic systemic fibrosis. Recently, it was shown that apparent diffusion coefficient (ADC) values can help distinguish between cancers, benign lesions and normal breast tissue. However, ADC maps are not sufficiently sensitive for establishing a stand alone method for breast cancer detection. [Eyal E., Shapiro-Feinberg M., Furman-Haran E., Grobgeld D., Golan T., Itzchak Y, Catane R, Papa M., Degani H. “A Novel MRI method for Breast Cancer Detection Based on Diffusion Tesor Tracking of the Ductal Tree.” Paper C-0329. Proc ISMRM, 19, May 2010].        
MRI advances, including parallel imaging, have enabled improvement in DWI utility:                The usefulness of DWI has already been established in the field of neuroradiology. Despite its excellent contrast resolution, DWI has the disadvantages of susceptibility and chemical shift artifacts. The introduction of the latest parallel imaging techniques, represented by SENSE technique, has solved these problems and enabled DWI to produce images clinically acceptable not only for neuroradiology but also for a variety of other fields. This is probably because the parallel imaging techniques are capable of reducing the number of phase encoding steps and the time required to fill the k-space, which may lead to the suppression of susceptibility and chemical artifacts. [Kuroki, Y, Nasu K, Kuroki S, Murakami K, Hayashi, T, Sekiguchi R, Nawano S. “Diffusion-weighted Imaging of Breast Cancer with the Sensitivity Encoding Techniques: Analysis of the Apparent Diffusion Coefficient Value,” Magnetic Resonance in Medical Sciences, Vol. 3, No. 2, p. 79-85: 2004].        
One inherent problem with breast DCE, the current standard method of magnetic resonance imaging, is that enhancing agents are routinely used off-label. Non-labeled use can result in inconsistency in how the contrast agent is administered. An important advantage of DWI/DTI is that it does not require an enhancing agent and problems associated with administration of the agent do not exist.
In spite of limited sensitivity of ADC maps, the information provided by ADC maps has the potential to lead to improved detection and diagnosis of breast cancer. In some cases, such as those in which the patients cannot tolerate the enhancing agent or where the high cost of acquiring enhanced images precludes their clinical application, DWI could provide an alternative to DCE.
One reported advantage of DWI over DCE is that diagnostic performance of DWI is similar for mass and non-mass-like enhancement type lesions and may be higher for smaller (<1 cm) versus larger lesions. [Partridge, S C, DeMartini W B, Kurland B F, Eby P R, White S W, Lehman C D. “Quantitative Diffusion-Weighted Imaging as an Adjunct to Conventional Breast MRI for Improved Positive Predictive Value,” AJR, December 2009; 193:1716-1722].
Moreover, DWI was found to perform equally well on invasive ductal and invasive lobular carcinoma. [Partridge, S C, DeMartini W B, Kurland B F, Eby P R, White S W, Lehman C D. “Quantitative Diffusion-Weighted Imaging as an Adjunct to Conventional Breast MRI for Improved Positive Predictive Value,” AJR December 2009; 193:1716-1722].
One primary reasons that DWI/DTI cannot currently be used in place of DCE for breast cancer screening is overlap of DWI intensity between benign and malignant lesions:                “However, because of considerable overlap in ADC of benign and malignant lesions, breast DWI must remain as a research tool until larger studies are performed to validate these findings.”        
[Partridge, S C, DeMartini W B, Kurland B F, Eby P R, White S W, Lehman C D. “Quantitative Diffusion-Weighted Imaging as an Adjunct to Conventional Breast MRI for Improved Positive Predictive Value,” AJR, December 2009; 193:1716-1722].
Overlap of benign and malignant lesions can be mitigated by the use of features that supplement the discrimination realized from analysis of differences in pixel intensity values on ADC map, as is presently done. Partridge and Baltzer investigated one such feature, fractional anisotropy (FA). Baltzer showed the following results of FA analysis of breasts.                “FA values of parenchyma were higher than those of benign lesions but at the same level of those of malignant lesions.” [Baltzer PAT, Schafer A, Dietzel M, Grassel D, Gajda M, Camara O, Kaiserr W A. “Diffusion Tensor magnetic Resonance Imaging of the Breast: A Pilot Study,” Eur Radiol, published online Jul. 29, 2010. In print]        
DWI can be acquired with a shorter acquisition time than is required for a DCE procedure that involves precontrast imaging, administration of contrast agent and saline push, and a sequence of dynamic contrast images that stretch over several minutes. In published literature, Partridge reported diffusion acquisition time of 2:40 minutes in both her DWI [and DTI studies. Partridge's DWI images were acquired using six directions. [Partridge, S C, Mullins C D, Kurland B F, Allain M D, DeMartini W B, Eby P R, Lehman C D. “Apparent Diffusion Coefficient Values for Discriminating Benign and Malignant Breast MRI Lesions: Effects of Lesion Type and Size.” AJR June 2010; 1994:1664-1673] [Partridge, S C, Ziadloo A, Murthy R S, White S W, Peacock S, Eby PR, DeMartini W B, Lehman C D. “Diffusion Tensor MRI: Preliminary Anisotropy Measures and Mapping of Breast Tumors,” Journal of Magnetic Resonance Imaging February 2010, 31:339-347]
The scientific basis of the proposed invention is based on two published results:                1. Study reported by Yili, et al., found that ADC values within 5 mm of a malignant lesion have cancer-like attributes, and that these cancer-like attributes tend to disappear as you move further from the lesion.[Yili Z, Xiaoyan H, Hongwen D, Yun Z, Xin C, Peng W, Youmin G. “The value of diffusion-weighted imaging in assessing the ACD changes of tissues adjacent to breast carcinoma.” BMC Cancer 2009, 9:18: 1-10. (available at http://www.biomedcentral.com/1471-2407/9/18)]        2. A study directed by the inventor that demonstrated that the sharpness of the margin or gradient of a breast lesion on MRI discriminates benign from malignant conditions.[Penn A I, Thompson S F, Brem R F, Lehman C, Weatherall P, Schnall M D, Newstead G M, Conant, E F Ascher S M, Morris E, Pisano E D. Morphologic Blooming in Breast MRI as a Characterization of Margin for Discriminating Benign from Malignant Lesions. Acad Radiol 2006; 13:1344-1354.]        “Others have shown that the signal loss from diffusion in vivo is driven by both perfusion and diffusion, with the changes at low b values dominated by perfusion and the higher values characterizing intra- and extra-cellular diffusion (17,39,40).” [S. C. Partridge, H. Rahbar, R. Murthy, X. Chai, B. F. Kurland, W. B. DeMartini, and C. D. Lehman. “Improved Diagnostic Accuracy of Breast MRI Through Combined Apparent Diffusion Coefficients and Dynamic Contrast-Enhanced Kinetics.” Magnetic Resonance in Medicine 65:1759-1767 (2011)].        
Cited references in above quote:
17. Sinha S, Lucas-Quesada FA, Sinha U, DeBruhl N, Bassett LW. In vivo diffusion-weighted MRI of the breast: potential for lesion characterization. J Magn Reson Imaging 2002;15:693-704.
39. Bogner W, Gruber S, Pinker K, Grabner G, Stadlbauer A, Weber M, Moser E, Helbich TH, Trattnig S. Diffusion-weighted MR for differentiation of breast lesions at 3.0 T: how does selection of diffusion protocols affect diagnosis? Radiology 2009;253:341-351.
40. Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 1988;168:497-505.